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检测心律的不稳定性。

Detecting instabilities of cardiac rhythm.

作者信息

Shusterman Vladimir, Aysin Benhur, Ermentrout G Bard, London Barry, Schwartzman David

机构信息

University of Pittsburgh, PA 15213, USA.

出版信息

J Electrocardiol. 2003;36 Suppl:219-26. doi: 10.1016/j.jelectrocard.2003.09.063.

Abstract

Diminished beat-to-beat variations in cardiac cycle lengths (CLs) are associated with poor prognosis after acute myocardial infarction and in patients with heart failure. Short-long-short sequences of cardiac cycles, or ultra-short rhythm instabilities, precede initiation of ventricular tachyarrhythmias in some patients. However, little is known about clinical or prognostic significance of abrupt short-term instabilities in CL (AICL) that occur minutes to hours before the event, in part because appropriate analytical methods are lacking. Although various techniques have been used to analyze CL changes, methods for analysis of AICL are limited. We compared performance of time domain, spectral, nonlinear, and pattern recognition techniques with respect to the detection and quantification of AICL. Because of high intra- and inter-subject variability of CL, pattern recognition techniques compared favorably to other studied methods. In continuous ambulatory ECG recordings, AICL occurred hours before spontaneous initiation of sustained atrial and ventricular arrhythmias in different patient populations. AICL were also found prior to the onset of spontaneous ventricular arrhythmias in a mouse model of congestive heart failure. To quantify AICL, we used the number of unstable orthogonal projection coefficients; this number gradually increased hours before the event. Removal of ectopic beats reduced but did not eliminate AICL. To illustrate potential physiological effects and temporal evolution of AICL, we used a simple, continuous, two-dimensional model of cardiac tissue governed by the Morris-Lecar equations. Computer simulations in this model showed that AICL may lead to gradual accumulation of spatial irregularities of the propagation wavefront giving rise to the initiation of reentry. Time-frequency analysis of the most significant eigenvectors of cardiac rhythm in subjects undergoing head-up tilt showed that AICL could indicate instabilities and unsuccessful adaptation of autonomic nervous system activity to physiological stimuli.

摘要

心动周期长度(CL)逐搏变化减小与急性心肌梗死后及心力衰竭患者的不良预后相关。在一些患者中,心动周期的短-长-短序列,即超短节律不稳定性,先于心室快速性心律失常的发作。然而,对于事件发生前几分钟到几小时出现的CL突然短期不稳定性(AICL)的临床或预后意义知之甚少,部分原因是缺乏合适的分析方法。尽管已使用各种技术来分析CL变化,但AICL的分析方法有限。我们比较了时域、频谱、非线性和模式识别技术在检测和量化AICL方面的性能。由于CL在个体内和个体间存在高度变异性,模式识别技术比其他研究方法表现更优。在连续动态心电图记录中,AICL在不同患者群体中自发持续性房性和室性心律失常发作前数小时出现。在充血性心力衰竭小鼠模型中,也在自发性室性心律失常发作前发现了AICL。为了量化AICL,我们使用了不稳定正交投影系数的数量;该数量在事件发生前数小时逐渐增加。去除异位搏动可减少但不能消除AICL。为了说明AICL的潜在生理效应和时间演变,我们使用了一个由Morris-Lecar方程控制的心组织简单、连续二维模型。该模型中的计算机模拟表明,AICL可能导致传播波前空间不规则性的逐渐积累,从而引发折返。对进行头高位倾斜试验的受试者心律最显著特征向量的时频分析表明,AICL可指示自主神经系统活动对生理刺激的不稳定性和适应失败。

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